Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Journal of Optimization Theory and Applications
A unifying geometric solution framework and complexity analysis for variational inequalities
Mathematical Programming: Series A and B
Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Journal of Optimization Theory and Applications
Long-step primal path-following algorithm for monotone variational inequality problems
Journal of Optimization Theory and Applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Introduction to Linear Optimization
Introduction to Linear Optimization
Operations Research
Robust solutions of uncertain linear programs
Operations Research Letters
Robust linear optimization under general norms
Operations Research Letters
Neural networks for solving second-order cone constrained variational inequality problem
Computational Optimization and Applications
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Using duality, we reformulate the asymmetric variational inequality (VI) problem over a conic region as an optimization problem. We give sufficient conditions for the convexity of this reformulation. We thereby identify a class of VIs that includes monotone affine VIs over polyhedra, which may be solved by commercial optimization solvers.